【摘要】：農(nóng)業(yè)是國民經(jīng)濟的基礎(chǔ)，，因此做好農(nóng)業(yè)相關(guān)工作在我國具有非常重要的社會意義。農(nóng)業(yè)保險有助于穩(wěn)定農(nóng)戶收入，迅速恢復農(nóng)業(yè)生產(chǎn)，實現(xiàn)國家對農(nóng)業(yè)產(chǎn)業(yè)的宏觀調(diào)控，是我國發(fā)展農(nóng)業(yè)的重要工具之一。然而由于我國政策性農(nóng)業(yè)保險開展工作的時間較短，有效的承保數(shù)據(jù)和損失數(shù)據(jù)非常有限，農(nóng)業(yè)保險費率的確定缺乏精準有效的技術(shù)支持。試點初期出于謹慎考慮，只能在全國采取統(tǒng)一費率。雖然易于操作，卻帶來了道德風險和逆向選擇問題。根據(jù)精算理論，如果承保對象足夠多，就可以根據(jù)風險特征的不同對個體進行風險分類，在此基礎(chǔ)上厘定各個風險等級的費率，消除道德風險和逆向選擇。 本文通過闡述并對比了目前比較流行的幾種風險分類的費率厘定方法，例如最小偏差法、非參數(shù)核密度法、分層貝葉斯模型以及廣義線性模型。通過結(jié)合湖南省政策性農(nóng)業(yè)保險關(guān)于種植業(yè)保險的經(jīng)營數(shù)據(jù)和氣象數(shù)據(jù)特征選擇了廣義線性混合模型對數(shù)據(jù)建模，認為廣義線性混合模型基于指數(shù)組分布，可以對非正態(tài)分布的數(shù)據(jù)進行回歸分析，但它又保留了很多正態(tài)線性回歸模型的常規(guī)思想，將復雜且相關(guān)的數(shù)據(jù)通過隨機效應進行擬合。同時結(jié)合廣義線性模型做實證分析，對湖南省種植業(yè)保險中棉花、油菜和水稻品種進行費率分類定價研究，通過實證分析得出廣義線性混合模型中湖南省種植業(yè)保險費率厘定的結(jié)果。最后對在湖南省具體實施這種定價方法過程中，要求農(nóng)業(yè)保險市場需要進行完善和改進的地方，提出了一些政策性建議。
[Abstract]:Agriculture is the foundation of the national economy, so it is of great social significance to do the agricultural work well in our country. Agricultural insurance is one of the important tools for the development of agriculture in China, which is helpful to stabilize the income of farmers, restore agricultural production quickly, and realize the macro-control of agricultural industry by the state. However, due to the short time of policy agricultural insurance in our country, the effective underwriting data and loss data are very limited, and the determination of agricultural insurance rate lacks accurate and effective technical support. Pilot early out of careful consideration, can only be adopted in the national flat rate. Although easy to operate, it brings moral hazard and adverse selection problems. According to actuarial theory, if there are enough insured objects, individuals can be classified according to different risk characteristics, and on this basis, the rate of each risk grade can be determined, and moral hazard and adverse selection can be eliminated. In this paper, several popular methods of rate determination for risk classification, such as minimum deviation method, nonparametric kernel density method, hierarchical Bayesian model and generalized linear model, are described and compared. Based on the management data and meteorological data characteristics of policy agricultural insurance in Hunan Province, the generalized linear mixed model is selected to model the data. It is considered that the generalized linear mixed model is based on exponential group distribution. Regression analysis of non-normal distribution data can be carried out, but it retains the conventional idea of many normal linear regression models, and the complex and relevant data are fitted by random effect. At the same time, with the generalized linear model to do empirical analysis, Hunan Province planting insurance in cotton, rape and rice varieties of the rate classification pricing research, Based on the empirical analysis, the results of determining the insurance rate of Hunan planting industry in the generalized linear mixed model are obtained. Finally, some policy suggestions are put forward in the course of implementing this pricing method in Hunan Province, which require the agricultural insurance market to be perfected and improved.
【學位授予單位】：湖南大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：F842.66

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